Conversion rate optimization: Difference between revisions

Revision as of 10:49, 15 October 2024

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== Methodology ==

Conversion rate optimization seeks to increase the percentage of website visitors that take a specific action (often submitting a web form, making a purchase, signing up for a trial, etc.) by methodically testing alternate versions of a page or process{{citation needed|date=February 2016}}<ref>{{Cite web |title=Conversion Rate Optimization |url=https://senate-marketing.com/search-engine-marketing/ |url-status=live |website=Senate Marketing}}</ref>, and through removing impediments to user experience and improving page loading speeds. In doing so, businesses are able to generate more leads or sales without investing more money on website traffic, hence increasing their marketing return on investment and overall profitability.<ref>{{cite book|last1=Goward|first1=Chris|url=https://books.google.com/books?id=2N1DwBhcMTkC|title=You Should Test That: Conversion Optimization for More Leads, Sales and Profit or The Art and Science of Optimized Marketing|date=2013|publisher=[[Wiley (publisher)|Wiley]]|isbn=9781118301302|___location=[[Hoboken, New Jersey]]|lccn=2012951871|oclc=1159801038}}</ref>

[[Statistical significance]] helps us understand that the result of a test is not achieved merely based on chance.

There are several approaches to conversion optimization with two main schools of thought prevailing in the last few years. One school is more focused on testing to discover the best way to increase website, campaign, or [[landing page]] conversion rates. The other school is focused on the pretesting stage of the optimization process.<ref>{{Cite book|last=McFarland|first=Colin|url=https://books.google.com/books?id=Z9B-7cHB5UwC|title=Experiment!: Website conversion rate optimization with A/B and multivariate testing|date=August 17, 2012|publisher=[[New Riders (publisher)|New Riders]]|isbn=9780133040081|___location=[[Berkeley, California]]|oclc=817741617|access-date=September 13, 2020|archive-date=May 7, 2021|archive-url=https://web.archive.org/web/20210507114802/https://books.google.com/books?id=Z9B-7cHB5UwC|url-status=live}}</ref> In this second approach, the optimization company will invest a considerable amount of time in understanding the audience and then creating a targeted message that appeals to that particular audience. Only then would it be willing to deploy testing mechanisms to increase conversion rates.

== Calculation of conversion rate ==